eda10ffe4b
This CL adds a test for the minimal sequence of compilation steps that need to be performed to compile the test while ensuring that macro declarations are compiled before any application. Change-Id: Icd6b9140e60d35d2b2b034c16e0807262f971418 Reviewed-on: https://dart-review.googlesource.com/c/sdk/+/220768 Reviewed-by: Jens Johansen <jensj@google.com> Commit-Queue: Johnni Winther <johnniwinther@google.com>
200 lines
6.4 KiB
Dart
200 lines
6.4 KiB
Dart
// Copyright (c) 2017, the Dart project authors. Please see the AUTHORS file
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// for details. All rights reserved. Use of this source code is governed by a
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// BSD-style license that can be found in the LICENSE.md file.
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library fasta.graph;
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import 'dart:math';
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import '../ast.dart';
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abstract class Graph<T> {
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Iterable<T> get vertices;
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Iterable<T> neighborsOf(T vertex);
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}
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/// [Graph] implementation using a collection of [Library] nodes as the graph
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/// vertices and using library dependencies to compute neighbors.
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///
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/// If [coreLibrary] is provided, it will be included in the neighbor of all
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/// vertices. Otherwise, `dart:core` will only be neighboring libraries that
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/// explicitly dependent on it.
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class LibraryGraph implements Graph<Library> {
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final Iterable<Library> libraries;
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final Library? coreLibrary;
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LibraryGraph(this.libraries, {this.coreLibrary});
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@override
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Iterable<Library> get vertices => libraries;
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@override
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Iterable<Library> neighborsOf(Library library) sync* {
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if (coreLibrary != null && library != coreLibrary) {
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yield coreLibrary!;
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}
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for (LibraryDependency dependency in library.dependencies) {
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yield dependency.targetLibrary;
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}
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}
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}
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/// Computes the strongly connected components of [graph].
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///
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/// This implementation is based on [Dijkstra's path-based strong component
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/// algorithm]
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/// (https://en.wikipedia.org/wiki/Path-based_strong_component_algorithm#Description).
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List<List<T>> computeStrongComponents<T>(Graph<T> graph) {
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List<List<T>> result = <List<T>>[];
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int count = 0;
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Map<T, int> preorderNumbers = <T, int>{};
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List<T> unassigned = <T>[];
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List<T> candidates = <T>[];
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Set<T> assigned = new Set<T>();
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void recursivelySearch(T vertex) {
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// Step 1: Set the preorder number of [vertex] to [count], and increment
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// [count].
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preorderNumbers[vertex] = count++;
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// Step 2: Push [vertex] onto [unassigned] and also onto [candidates].
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unassigned.add(vertex);
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candidates.add(vertex);
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// Step 3: For each edge from [vertex] to a neighboring vertex [neighbor]:
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for (T neighbor in graph.neighborsOf(vertex)) {
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int? neighborPreorderNumber = preorderNumbers[neighbor];
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if (neighborPreorderNumber == null) {
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// If the preorder number of [neighbor] has not yet been assigned,
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// recursively search [neighbor];
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recursivelySearch(neighbor);
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} else if (!assigned.contains(neighbor)) {
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// Otherwise, if [neighbor] has not yet been assigned to a strongly
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// connected component:
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//
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// * Repeatedly pop vertices from [candidates] until the top element of
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// [candidates] has a preorder number less than or equal to the
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// preorder number of [neighbor].
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while (preorderNumbers[candidates.last]! > neighborPreorderNumber) {
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candidates.removeLast();
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}
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}
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}
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// Step 4: If [vertex] is the top element of [candidates]:
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if (candidates.last == vertex) {
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// Pop vertices from [unassigned] until [vertex] has been popped, and
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// assign the popped vertices to a new component.
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List<T> component = <T>[];
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while (true) {
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T top = unassigned.removeLast();
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component.add(top);
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assigned.add(top);
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if (top == vertex) break;
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}
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result.add(component);
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// Pop [vertex] from [candidates].
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candidates.removeLast();
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}
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}
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for (T vertex in graph.vertices) {
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if (preorderNumbers[vertex] == null) {
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recursivelySearch(vertex);
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}
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}
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return result;
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}
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/// A [Graph] using strongly connected components, as computed by
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/// [computeStrongComponents], as vertices. Neighbors are computed using the
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/// neighbors of the provided [subgraph] which was used to compute the strongly
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/// connected components.
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class StrongComponentGraph<T> implements Graph<List<T>> {
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final Graph<T> subgraph;
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final List<List<T>> components;
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final Map<T, List<T>> _elementToComponentMap = {};
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final Map<List<T>, Set<List<T>>> _neighborsMap = {};
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StrongComponentGraph(this.subgraph, this.components) {
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for (List<T> component in components) {
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for (T element in component) {
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_elementToComponentMap[element] = component;
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}
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}
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}
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Set<List<T>> _computeNeighborsOf(List<T> component) {
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Set<List<T>> neighbors = {};
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for (T element in component) {
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for (T neighborElement in subgraph.neighborsOf(element)) {
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List<T> neighborComponent = _elementToComponentMap[neighborElement]!;
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if (component != neighborComponent) {
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neighbors.add(neighborComponent);
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}
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}
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}
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return neighbors;
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}
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@override
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Iterable<List<T>> neighborsOf(List<T> vertex) {
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return _neighborsMap[vertex] ??= _computeNeighborsOf(vertex);
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}
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@override
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Iterable<List<T>> get vertices => components;
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}
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/// Returns the non-cyclic vertices of [graph] sorted in topological order.
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///
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/// If [indexMap] is provided, it is filled with "index" of each vertex.
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/// If [layers] is provided, it is filled with a list of the vertices for each
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/// "index".
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///
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/// Here, the "index" of a vertex is the length of the longest path through
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/// neighbors. For vertices with no neighbors, the index is 0. For any other
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/// vertex, it is 1 plus max of the index of its neighbors.
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List<T> topologicalSort<T>(Graph<T> graph,
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{Map<T, int>? indexMap, List<List<T>>? layers}) {
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List<T> workList = graph.vertices.toList();
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indexMap ??= {};
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List<T> topologicallySortedVertices = [];
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List<T> previousWorkList;
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do {
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previousWorkList = workList;
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workList = [];
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for (int i = 0; i < previousWorkList.length; i++) {
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T vertex = previousWorkList[i];
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int index = 0;
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bool allSupertypesProcessed = true;
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for (T neighbor in graph.neighborsOf(vertex)) {
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int? neighborIndex = indexMap[neighbor];
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if (neighborIndex == null) {
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allSupertypesProcessed = false;
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break;
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} else {
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index = max(index, neighborIndex + 1);
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}
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}
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if (allSupertypesProcessed) {
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indexMap[vertex] = index;
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topologicallySortedVertices.add(vertex);
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if (layers != null) {
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if (index >= layers.length) {
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assert(index == layers.length);
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layers.add([vertex]);
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} else {
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layers[index].add(vertex);
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}
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}
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} else {
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workList.add(vertex);
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}
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}
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} while (previousWorkList.length != workList.length);
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return topologicallySortedVertices;
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}
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